2022

  • Grabinger, F. Hauser, and J. Mottok. Accessing the presentation of causal graphs and an application of gestalt principles with eye tracking. In Proceedings of the 29th IEEE International Conference on Software Analysis, Evolution, and Reengineering (SANER 2022), ISBN 978-1-6654-3787-5, pages 1267-1274. IEEE, New York, NY, USA, March 2022.

2023

  • D. Bittner, F. Hauser, V. K. Nadimpalli, L. Grabinger, S. Staufer, J. Mottok,. Towards Eye Tracking based Learning Style Identification. In Proceedings of the 5th European Conference on Software Engineering Education (pp. 138-147), Juni 2023.
  • D. Bittner, R. R. Hendricks, J Mottok. In-depth Benchmarking of Transfer Learning Techniques for Improved Bottle Recognition. In 2023 IEEE 13th International Conference on Pattern Recognition Systems (ICPRS) (pp. 1-6), Juli 2023. IEEE.
  • L. Grabinger, F. Hauser, and J. Mottok, “On the perception of graph layouts,” Journal of Software: Evolution and Process (J. Softw. Evol. Proc.), vol. 2023, no. e2599, pp. 1-18, Jul. 2023, doi: 10.1002/smr.2599.
  • A. Homann, L. Grabinger, F. Hauser, and J. Mottok, “An eye tracking study on MISRA C coding guidelines,” in Proc. 5th European Conf. Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 130-137, doi: 10.1145/3593663.3593671. (BEST PAPER AWARD)
  • L. Grabinger, F. Hauser, and J. Mottok, “Evaluating graph-based modeling languages,” in Proc. 5th European Conf. Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 120-129, doi: 10.1145/3593663.3593664.
  • F. Hauser, L. Grabinger, and J. Mottok, “Something short gets even shorter: Adapting the LIST-K for the use in an online learning management system,” in Proc. 5th European Conf. Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 65-72, doi: 10.1145/3593663.3593684.
  • V. Nadimpalli, F. Hauser, D. Bittner, L. Grabinger, S. Staufer, and J. Mottok, “Systematic literature review for the use of AI based techniques in adaptive learning management systems,” in Proc. 5th European Conf. Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 83-92, doi: 10.1145/3593663.3593681.
  • F. Hauser, L. Grabinger, J. Mottok, S. Jahn, and V. Nadimpalli, “The expert’s view: Eye movement modeling examples in software engineering education,” in Proc. 5th European Conf. Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 148-152, doi: 10.1145/3593663.3593683.
  • F. Bugert, L. Grabinger, D. Bittner, F. Hauser, V. Nadimpalli, S. Staufer, and J. Mottok, “Towards learning style prediction based on personality,” in Proc. 5th European Conf. Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 48-55, doi: 10.1145/3593663.3593682.
  • F. Hauser, L. Grabinger, J. Mottok, and H. Gruber, “Visual expertise in code reviews: Using holistic models of image perception to analyze and interpret eye movements,” in Proc. 2023 Symp. Eye Tracking Research and Applications (ETRA 2023), Tübingen, Germany, June 2023, pp. 1-7, doi: 10.1145/3588015.3589189.
  • S. Staufer, F. Hauser, D. Bittner, V. Nadimpalli, L. Grabinger, and J. Mottok, “Learning elements in online learning management systems,” in ICERI2023 Proceedings, vol. 10, IATED Digital Library, t.b.p.
  • T. Ezer, M. Greiner, L. Grabinger, F. Hauser, J. Mottok. Eye tracking as Technology in education: data quality analysis and improvements. In ICERI2023 Proceedings, vol. 10, IATED Digital Library.
  • V. Nadimpalli, F. Bugert, D. Bittner, F. Hauser, L. Grabinger, S. Staufer, J. Mottok (2023) Towards Personalized Learning Paths in Adaptive Learning Management Systems: Bayesian Modelling of Psychological Theories, ICERI2023 Proceedings, pp. 4593-4603,DOI: https://doi.org/10.21125/iceri.2023.1144.
  • Bittner, D., Ezer, T., Grabinger, L., Hauser, F., & Mottok, J. (2023). Unveiling the secrets of learning styles: decoding eye movements via machine learning. In ICERI2023 Proceedings (pp. 5153-5162). IATED.
  • M. Normann, J. Haug, Y. Valencia, J. Abke, G. Hagel, Adaptive Learning Path Sequencing Based on Learning Styles within N-Dimensional Spaces, 5th European Conference on Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 56-64. doi: 10.1145/3593663.3593676
  • Sapsai, Y. P. Valencia Usme, J. Abke, Learning Analytics Dashboard for Educators: Proposed Project to Design with Pedagogical Background, 5th European Conference on Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 38-47, doi:10.1145/3593663.3593686
  • Y. P. Valencia Usme, M. Normann, I. Sapsai, J. Abke, A. Madsen, G. Weidl, Learning Style Classification by Using Bayesian Networks Based on the Index of Learning Style, 5th European Conference on Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 73-82, doi:10.1145/3593663.3593686.
  • M. Normann, Students’ Acceptance of Explainable, AI-Based Learning Path Recommendations in an Adaptive Learning System, 2023, doi:10.18420/ki2023-dc-07.
  • J Haug, D. Fischer, G. Hagel, „Development of a Short Form of the Index of Learning Styles for the Use in Adaptive Learning Systems“, 5th European Conference on Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 73-82, doi: 10.1145/3593663.3593675.
  • D. Bigler, G. Hagel, “Technical Report: Define a customized course and import it into Moodle without changes to the configuration of the Moodle system”, 5th European Conference on Software Engineering Education (ECSEE 2023), Seeon, Germany, June 2023, pp. 73-82, doi: 10.1145/3593663.3593668.

2024

  • L. Grabinger and J. Mottok. Statistical analysis of eye movement data for beginners. In Proceedings of Mensch und Computer 2024 (MuC ’24), pages 21-28, ACM, Karlsruhe, Germany, September 2024.
  • L. Grabinger, T. Ezer, F. Hauser and J. Mottok. The impact of eyenalyzer. In Proceedings of the 17th annual International Conference of Education, Research and Innovation (ICERI ’24), pages 1-7, IATED, Seville, Spain, November 2024.
  • L. Grabinger and J. Mottok. On selecting hypothesis tests for group difference. In Proceedings of the 17th annual International Conference of Education, Research and Innovation (ICERI ’24), pages 1-7, IATED, Seville, Spain, November 2024.
  • Staufer, S., Bugert, F., Hauser, F., Grabinger, L., Ezer, T., Nadimpalli, V. K., & Mottok, J. (2024). Tyche Algorithm: Markov Models for Generating Learning Paths in Learning Management Systems. In INTED2024 Proceedings (pp. 4195-4205). IATED.
  • Röhrl, S., Staufer, S., Nadimpalli, V. K., Bugert, F., Hauser, F., Grabinger, L., & Mottok, J. (2024). Pythia-AI suggested Individual Learning Paths for Every Student. In INTED2024 Proceedings (pp. 2871-2880). IATED.
  • Staufer, S., Hauser, F., Grabinger, L., Bittner, D., Nadimpalli, V. K., Bugert, F., & Mottok, J. (2024). Learning Elements in LMSA Survey Among Students. In INTED2024 Proceedings (pp. 4224-4231). IATED.
  • Bugert, F., Staufer, S., Bittner, D., Nadimpalli, V. K., Ezer, T., Hauser, F., & Mottok, J. (2024, May). Ariadne’s Thread for Unravelling Learning Paths: Identifying Learning Styles via Hidden Markov Models. In 2024 IEEE Global Engineering Education Conference (EDUCON) (pp. 1-7). IEEE.
  • S. Staufer, F. Bugert, F. Hauser, L. Grabinger, T. Ezer, V.K. Nadimpalli, D. Bittner, S. Röhrl, J. Mottok (2024) Tyche Algorithm: Markov Models for generating learning paths in learning management systems, INTED2024 Proceedings, pp. 4195-4205.
  • S. Staufer, F. Hauser, L. Grabinger, D. Bittner, V. K. Nadimpalli, F. Bugert, T. Ezer, S. Röhrl, J. Mottok (2024) Learning elements in LMS – A survey among students, INTED2024 Proceedings, pp. 4224-4231.
  • S. Staufer, F. Hauser, T. Ezer, L. Grabinger, V. K. Nadimpalli, S. Röhrl, F. Bugert, D. Bittner, J. Mottok (2024) Evaluation of the learning management system pythia, EDULEARN24 Proceedings, pp. 9089-9098.
  • S. Staufer, V.K. Nadimpalli, F. Hauser, D. Bittner, L. Grabinger, F. Bugert, T. Ezer, S. Röhrl, J. Mottok (2024) Persistence of questionnaire data on learning styles, learning strategies and personality traits, ICERI2024 Proceedings, S. Staufer, V.K. Nadimpalli, F. Hauser, D. Bittner, L. Grabinger, F. Bugert, T. Ezer, S. Röhrl, J. Mottok (2024) Persistence of questionnaire data on learning styles, learning strategies and personality traits, ICERI2024 Proceedings, pp. 6310-6319.
  • S. Röhrl, S. Staufer, V.K. Nadimpalli, F. Bugert, F. Hauser, L. Grabinger, D. Bittner, T. Ezer, and J. Mottok. Pythia – AI suggested individual learning paths for every student. In Proceedings of INTED2024, pp. 2871-2880, Valencia, Spain, March 2024.
  • F. Hauser. Visuelle Expertise bei Code Reviews. Universitätsverlag der Universität Regensburg, Regensburg, Germany, November 2024.
  • J. Mottok, F. Hauser, L. Grabinger, T. Ezer and F. Engl. An Educational Perspective on Eye Tracking in Engineering Sciences. In Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, pages 1-7, ACM, Glasgow, UK, June 2024.
  • F. Hauser, L. Grabinger, T. Ezer, J. Mottok and H. Gruber, Analyzing and Interpreting Eye Movements in C++: Using Holistic Models of Image Perception, In Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, pages 1-7, ACM, Glasgow, UK, June 2024.
  • F. Hauser, L. Grabinger, T. Ezer, J. Mottok and H. Gruber, Integrating Deliberate Practice into Software Engineering Education. In Proceedings IATED International Conference of Education, Research and Innovation, tbp, IATED, Seville, Spain, November 2024.
  • T. Ezer, L. Grabinger, F. Hauser, S. Staufer, J. Mottok (2024) Eye Tracking metrics for distinguishing global and focal gaze patterns: A systematic literature review, INTED2024 Proceedings, pp. 3005-3014.
  • T. Ezer, L. Grabinger, F. Hauser, S. Staufer, J. Mottok (2024) Eye Tracking as technology in education: Further investigation of data quality and improvements, INTED2024 Proceedings, pp. 2955-2961. (t.b.p.)
  • T. Ezer, M. Plößl, L. Grabinger, D. Bittner, S. Staufer, V. Nadimpalli, F. Bugert, F. Hauser, J. Mottok (2024) Deep learning for eye movement classification, ICERI2024 Proceedings.
  • V.K. Nadimpalli, F. Bugert, D. Bittner, T. Ezer, S. Staufer, S. Röhrl, F. Hauser, L. Grabinger, R. Maier, J. Mottok, Probabilistic Machine Learning for Simulating Complex Learner Profiles, 21st International Conference on Information Technology Based Higher Education and Training (ITHET). IEEE, Paris, France, 2024, (t.b.p.)
  • V.K. Nadimpalli, S. Staufer, T, Ezer, F. Bugert, D. Bittner, S. Röhrl, F. Hauser, L. Grabinger, R. Maier, J. Mottok, et al., Probabilistic Machine Learning for Simulating Complex Learner Profiles, 17th annual International Conference of Education, Research and Innovation (ICERI). IATED, Sevilla, Spain, 2024, (t.b.p.).
  • J. Haug, I. Sapsai, I. Hock, J. Abke, G. Hagel, Evaluating an AI-based Adaptive Learning System: Goals, Methods and Initial Results, 16th annual International Conference on Education and New Learning Technologies (EDULEARN), IATED, 2024, pp. 3157-3166.  doi: 10.21125/edulearn.2024.0834.
  • Sapsai, J. Haug, J. Abke, G. Hagel, G. Weidl, Identifying Student Emotions in an Adaptive Learning System with a Bayesian Network Model, 17th annual International Conference of Education, Research and Innovation (ICERI), IATED, Sevilla, Spain, 2024, pp. 4829-4837. doi: 10.21125/iceri.2024.1192.
  • D. Bigler, J. Manz, K. Lee, D. Fischer, G. Hagel, Learning Environment Interoperability in Software Engineering Education, 36th International Conference on Software Engineering Education and Training (CSEE&T), IEEE, Würzburg, Germany, 2024, doi: 10.1109/CSEET62301.2024.10663056.
  • D. Fischer, G. Hagel, Enhancing NLP-Based Educational Assessment: A Node-Based Graph Approach for Analyzing Freeform Student Texts, 47th MIPRO ICT and Electronics Convention (MIPRO), IEEE, Opatija, Croatia, 2024, pp. 108-113, doi: 10.1109/MIPRO60963.2024.10569607.